Genomic Screening

Share

My greatest interest is in the correlation of genomic information with the medical record both for diagnostic purposes and for the data mining that will be available from the resulting combined databases, both clinical and genomic.

The present overly cautious approach to bio-molecular testing -- that is testing for suspected variants on the basis of clinical suspicion -- limits the science of data mining. With this limitation, any additional abnormalities are viewed as incidental to a skewed population of suspected cases.

Studies based on massive insurance data are flawed from the beginning. Insurance diagnosis is entered according to the studies the clinician wishes to do in order to meet the diagnostic requirements for the test -- representing tentative diagnosis, a speculative or at best a differential diagnosis. Often-times the insurance clerk picks a diagnosis that approximates the physician’s but which better meets the requirements for reimbursement.

The screening of all patients -- with their permission -- on the other hand, will build a correlation between molecular and clinical findings that is more valid for research and can more cleanly contribute to a differential diagnosis and differential risk factors.

We have only scratched the surface of the information that will be forthcoming from molecular biology. We need to open the flood-gate of genomic information for clinical correlation with statistical analysis on an ongoing real-time basis. The data from multiple clinics and private practices could be combined anonymously and indefinitely in a medical school or trusted institution; its value will grow with time. It’s diagnostic and correlative legs will reinforce one another with time.

When I sold my practice/clinic there were over fifty thousand charts, a gold mine for data mining. Most old medical records are ultimately neglected or lost as were mine. This is front line data, which differs from the national or regional data collected by institutions. It is local data and as such more personal and thus more explicit and if analyzed real-time, more critical.

This process of learning as we go is the scientific method and the basis of medical science. The learning process should extend to all physicians willing to include it in their practice. I feel passionate about working in a team setting, to bring genetic screening to the medical clinic, the private practice and the community.

The goal would be the free distribution of a standalone software application that would securely store the whole genome of patients, whilst correlating it with that patient’s real-time clinical data. More relevant, however, the continuing growth in data-mining in the two matched databases will lead to new insights and certainties not otherwise rapidly achievable.

As an aside one might observe that evidence based protocols place more emphasis on treatment than on diagnosis. Missed and wrong diagnoses remain a major problem, a fact partially borne out by the US’s poor ranking in the Global Burden of Disease (GBD) studies. A byproduct of this initiative will lead to enhanced diagnostic decision support and a quantum improvement in patient care and outcome.